An anonymous reader quotes a report from The Verge: Discord has identified approximately 70,000 users that may have had their government ID photos exposed as part of a customer service data breach announced last week, spokesperson Nu Wexler tells The Verge. A tweet by vx-underground said that the company was being extorted over a breach of its Zendesk instance by a group claiming to have "1.5TB of age verification related photos. 2,185,151 photos." In its announcement last week, Discord said that information like names, usernames, emails, the last four digits of credit cards, and IP addresses also may have been impacted by the breach. "All affected users globally have been contacted and we continue to work closely with law enforcement, data protection authorities, and external security experts," said Wexler. "We've secured the affected systems and ended work with the compromised vendor. We take our responsibility to protect your personal data seriously and understand the concern this may cause."

Read more of this story at Slashdot.

Microsoft is getting ready to release a new OneDrive app on Windows next year that will include a photo gallery, people view, AI-powered slideshows, and editing features. It’s part of a number of new features coming to OneDrive in the coming months, including a new Photos Agent and AI-powered mobile editing.

The new OneDrive app on Windows is a big redesign compared to the existing desktop app. Instead of a tiny flyout on the taskbar, it’s a full app that’s a lot more like OneDrive’s mobile app. It includes a new gallery view of all your cloud photos and a dedicated people view that detects faces in photos and lets you name them.

OneDrive on Windows will also work with local photos soon, letting you edit images and then keep them locally on a drive or upload them to Microsoft’s cloud storage service.

Microsoft is also adding even more Copilot integration into OneDrive, with a new Photos Agent that will be available for Microsoft 365 Copilot and Microsoft 365 Premium subscribers. It’s like a chatbot for your photos, letting you ask for a collection of holiday photos, or to recall particular points in time. Copilot will then find photos and allow you to build albums, too.

OneDrive on iOS and Android is also getting AI mobile editing soon, with the ability to turn photos into animated styles. You’ll be able to easily clean up blurry or duplicated shots from the mobile app, and a new moments tab has already started rolling out that surfaces older photos and “on this day” memories.

Microsoft has also launched a big update to the way OneDrive users share documents. A new “hero link” feature means you can simply copy the URL of a OneDrive document instead of having to share special links to people. It’s identical to the way Google Docs has operated for years, and finally makes it easy for people to request access to files instead of getting an ugly access denied message.

iFixit has broken down Meta’s Ray-Ban Display glasses, revealing that the tech inside isn’t what makes them special — it’s the glassmaking. iFixit explains that the glass lenses use a reflective geometric waveguide system that bounces some of the light out to the wearer’s eyes at specific angles via partially reflective mirrors, which helps prevent other people from getting a glimpse of the screen when they look at you.

This works alongside the micro-projector in the right arm, a liquid crystal on silicon (LCoS) device that bounces light from three LEDs to provide a 600×600-pixel grid image. The geometric waveguide lenses differ from older “diffractive” systems used in other AR glasses, which bend and split light instead, sometimes causing the user to see little rainbow artifacts or flash “eye glow” light at onlookers. The downside is that the glass used in the Ray-Ban Display is expensive to manufacture, with iFixit speculating that Meta may be selling the glasses at a loss. 

iFixit had to split the arms and frame in half to conduct the teardown, noting that Meta didn’t provide a means to clip them back together again for situations like battery replacements. “Any repairs here are going to need specialized skills and specialized tools,” iFixit teardown tech  Shahram Mokhtari said in the video, adding that it’s “very clear that the first iterations of these smartglasses are going to be unrepairable.”

The wait(list) is over for The Browser Company’s Dia, its AI-powered follow-up to Arc. If you have a Mac, that is.

The Browser Company, which was acquired by software giant Atlassian for $610 million last month, said “Dia is now open to everyone on MacOS.” It’s the first time Dia has been widely available since launching in June. It’s one of several tools from firms like Google, Opera, and Perplexity making AI central to surfing the web with features like chatbot assistants and AI-powered shortcuts. 

There’s still no word on when or if The Browser Company plans on making Dia available on Windows. 

While using LLMs to judge LLM outputs might seem like the fox guarding the henhouse, turns out it works pretty well (and scales better than humans).

For years, SaaS companies cruised on easy per-seat pricing and almost-free scaling. Enter AI: every query burns power, every model costs cash, and suddenly startups are in a pricing puzzle.

In his talk Pricing for AI Agents at the How to Web Conference 2025 in Bucharest, Emanuel Martonca (Founder, Pricing Strategist at Soft Fight) dives into why traditional SaaS pricing no longer works – and what it takes to build sustainable business models in the AI era.

Let’s start with an example

Emanuel opens his talk with a simple story:

Imagine you’re an angel investor having lunch with a founder who’s built an AI platform that helps large companies map their employees’ skills.

The founder explains that the tool lets sales teams quickly find experts in niche technologies across the organization, making it easier to sell IT services.

In a company of 10.000 people, sales representatives are often far removed from the engineers doing the actual work. So, when a client in New York asks about a specific technology, the salesperson might have no idea whether anyone in the company has that expertise – or even where to find them.

The founder claims his AI solves this problem in days, not months, and points out the lucrative potential. After all, some companies currently pay almost $400.000 annually for software solving the same problem.

However, Emanuel warns – there are couple of critical considerations when thinking about AI pricing.

Think SaaS, think small. Think AI, think big (and expensive)

AI is fundamentally different from traditional SaaS, explains Martonca. While SaaS benefits from near-zero marginal costs for additional users and high gross margins, AI is computationally expensive:

A single AI query can consume ten times more energy than a Google search. Such costs must be considered in pricing, along with other factors like marketing, positioning, differentiation, and risk

Unlike SaaS, where the main concern might be looking like a glorified spreadsheet, AI introduces far more complex risks.

Traditional SaaS frameworks and mental models don’t translate to AI startups – they require a different approach. In particular, common SaaS seat-based subscription models often fail in the AI context.

As Martonca highlights, AI frequently replaces the very people you might charge for, making seat-based pricing impractical.

Moreover, many AI projects, proofs of concept, pilots, or experiments never reach production:

Every AI pilot that doesn’t go to production represents lost revenue for software vendors, and AI accelerates development, reducing the need for large teams – further impacting legacy software revenues.

Price the problem, not the technology!

Currently, there is no standard model for AI pricing.

Unlike SaaS, where “good-better-best” packages and per-seat subscriptions were well-established, AI pricing is complex and still experimental:

You can price by input, output, outcome, or performance. The choice depends heavily on the problem being solved and the client’s perceived value, rather than purely on technological complexity.

Many founders get caught up in explaining how their AI works so they talk about the models, the architecture, the agents, but clients care most about solving a business problem.

A central lesson is to price the problem, not the technology, Emanuel points out.

In the skills-matching example, instead of charging for the software or the AI engine, the vendor could charge for each successful match of employee to project. This approach shifts risk to the vendor, but aligns price with the value delivered to the client.

Companies used to be product- or service-focused. Not anymore.

Emanuel also highlights the blurring line between products and services in AI. Traditionally, companies were either product-focused or service-focused. AI challenges this distinction.

OpenAI, for example, sells consulting services alongside its technology platform. Delivering outcomes and real business results has become the primary source of value, not just providing access to software.

AI budgets also differ from traditional IT budgets:

SaaS historically took money from IT departments. AI often taps into HR or services budgets, which are significantly larger.

Always start with the customer and their problem

For both startups and established companies, Emanuel’s advice is clear: start with the customer and the problem they need solved. Identify what they value and what they’re willing to pay for – only then design a solution and assess its economic viability.

Most AI vendors currently use a hybrid model: a flat base price for platform access, some included usage, and additional charges based on usage or tokens. It’s a pragmatic – if temporary – solution in an environment full of unknowns. Yet the fundamental principles of pricing still apply:

Understand the value delivered, choose the right metric for your model, and price according to the problem solved, not just the technology deployed.

This is important beacuse getting pricing wrong can be fatal. Companies that adapt their models to reflect value and outcomes, rather than legacy SaaS logic, will be best positioned to succeed in this new era.

The post You Built an AI Agent – But How Do You Price It? appeared first on ShiftMag.